V3 Sequences of Paired HIV-1 Isolates from Blood and Cerebrospinal Fluid Cluster According to Host and Show Variation Related to the Clinical Stage of Disease

Keys, Barbara; Karis, Jenny; Fadeel, Bengt; Valentı́n, Antonio; Norkrans, Gunnar; Hagberg, Lars; Chiodi, Francesca

doi:10.1006/viro.1993.1503

Cited by 84 publications

(59 citation statements)

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“…3 and 6), consistent with a large number of previous studies (6,22,24,27,33,34,36,43,45,52,53,56,58,62,63,74,81). While this overwhelming body of evidence of compartmentalization suggests the existence of adaptive differences involved in infection of the CNS, it has been alternatively hypothesized that differences in the rates of virus turnover in different cell types may lead to the population differences observed between brain and lymph node, given the rapid temporal change in HIV populations over time in peripheral blood mononuclear cells and other lymphoid cell types (45).…”

Section: Discussionsupporting

confidence: 89%

Identification of Shared Populations of Human Immunodeficiency Virus Type 1 Infecting Microglia and Tissue Macrophages outside the Central Nervous System

Wang

Donaldson

Brettle³

et al. 2001

J Virol

184

180

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Infection of microglia and other cells of the macrophage/monocyte lineage in the central nervous system (CNS) by human immunodeficiency virus type I (HIV-1) underlies the development of giant cell encephalitis (GCE). It is currently unknown whether GCE depends on the emergence of virus populations specifically adapted to replicate in cells of the monocyte/macrophage lineage and whether this also leads to the specific targeting of macrophages in other nonlymphoid tissues. Autopsy samples from lymph node, brain (frontal region), lung, and full-thickness colon sections were obtained from nine study subjects with GCE and from nine without. The two groups showed no significant differences in CD4 counts, disease progression, or treatment history before death. Genetic relatedness between variants recovered from lymph node and nonlymphoid tissues was assessed by sequence comparison of V3 and p17 gag regions using a newly developed method that scores the sample composition at successive nodes in a neighbor-joining tree. The association index enabled objective, numerical comparisons on the degree of tissue compartmentalization to be made. High proviral loads and p24 antigen expression in the brain were confined to the nine individuals with GCE. GCE was also associated with significantly higher proviral loads in colon samples (median of the GCE ؉ group: 1,010 copies/10 6 cells; median of GCE ؊ group, 10/10 6 cells; P ‫؍‬ 0.006). In contrast, there were no significant differences in proviral load between the GCE ؉ and GCE ؊ groups in lymph node or lung samples, where HIV infection was manifested predominantly by infiltrates of lymphoid cells. V3 sequences from brain samples of individuals with GCE showed the greatest compartmentalization from those of lymph node, although samples from other tissues, particularly the colon, frequently contained variants phylogenetically related to those found in brain. The existence of shared, distinct populations of HIV specifically distributed in cells of the monocyte/ macrophage lineage was further indicated by immunocytochemical detection of CD68 ؉ , multinucleated giant cells expressing p24 antigen in samples of lung and colon in two individuals with GCE. This study provides the basis for future investigation of possible phenotypic similarities that underline the shared distributions of HIV variants infecting microglia and tissue macrophages outside the CNS.

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Section: Discussionsupporting

confidence: 89%

Identification of Shared Populations of Human Immunodeficiency Virus Type 1 Infecting Microglia and Tissue Macrophages outside the Central Nervous System

Wang

Donaldson

Brettle³

et al. 2001

J Virol

184

180

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“…Other studies also found distinct V3 sequence populations in serum and CSF from some patients, but not from others. No variable has yet been found to be associated with this difference, neither Short communication disease stage (Keys et al, 1993), tropism of the isolated virus in peripheral blood monocytes (PBMCs) culture (Keys et al, 1993), nor the presence or absence of ADC (this study). It is conceivable that the population differences simply reflect a time-lag, much as has been shown to exist between virions from serum and proviral DNA from infected PBMCs (Simmonds et al, 1991).…”

mentioning

confidence: 67%

“…There have been a number of earlier searches for differences between HIV envelope sequences found in different tissue types, both in the V3 region (Keys et al, 1993;Epstein et al, 1991;Korber et al, 1994), the V4 region and the CD4 binding site (Korber et al, 1994;Pang et al, 1991), and in gp41 (Steuler et al, 1992). The same picture emerges from all these studies: in some patients, the populations of variants found in different tissue types are distinct, in others they are similar.…”

mentioning

confidence: 99%

Differences in human immunodeficiency virus type 1 V3 sequences from patients with and without AIDS dementia complex

Kuiken

Goudsmit²,

Weiller³

et al. 1995

Journal of General Virology

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Paired serum and cerebrospinal fluid (CSF) samples from 10 AIDS patients with and 10 without AIDS dementia complex (ADC) were studied, in an attempt to uncover ADC-associated variation in V3 sequences. Sequences were obtained from four of the patients with and eight of those without ADC. Comparison of the sequences using a resampling technique revealed a significant ADC-associated difference occurring at several amino acid positions. Results from serum and CSF sequences were comparable. These differences may indicate that the virus found in ADC and that in non-ADC patients have different biological properties. Comparison of serum versus CSF sequences within samples from both ADC and non-ADC patients, using the same resampling technique, revealed no clear distinctions. In some patients, the sequence populations in serum and CSF were completely distinct, while in others, there was no difference in distribution. These patterns were not associated with ADC.

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“…This variation has important consequences. It allows the virus to evolve to infect different cell types (9,20,30) and to rapidly become resistant to otherwise highly effective antiviral drugs (10,47,50); it may play a role in evading the immune system (4,56,73,79). Furthermore, its high mutation rate (estimated to average about 3 ϫ 10 Ϫ5 per nucleotide site per replication cycle [49]), large population size (variously estimated from about 10 7 to 10 8 productively infected cells), and continuous steady state, in which the large majority of virions and productively infected cells turns over every day (25,77), create a situation which, at least in principle, is amenable to (and requires) mathematical modeling.…”

Section: Introductionmentioning

confidence: 99%

Transition between Stochastic Evolution and Deterministic Evolution in the Presence of Selection: General Theory and Application to Virology

Rouzine

Rodrigo

Coffin

2001

Microbiol Mol Biol Rev

159

153

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We present here a self-contained analytic review of the role of stochastic factors acting on a virus population. We develop a simple one-locus, two-allele model of a haploid population of constant size including the factors of random drift, purifying selection, and random mutation. We consider different virological experiments: accumulation and reversion of deleterious mutations, competition between mutant and wild-type viruses, gene fixation, mutation frequencies at the steady state, divergence of two populations split from one population, and genetic turnover within a single population. In the first part of the review, we present all principal results in qualitative terms and illustrate them with examples obtained by computer simulation. In the second part, we derive the results formally from a diffusion equation of the Wright-Fisher type and boundary conditions, all derived from the first principles for the virus population model. We show that the leading factors and observable behavior of evolution differ significantly in three broad intervals of population size, N. The “neutral limit” is reached when N is smaller than the inverse selection coefficient. When N is larger than the inverse mutation rate per base, selection dominates and evolution is “almost” deterministic. If the selection coefficient is much larger than the mutation rate, there exists a broad interval of population sizes, in which weakly diverse populations are almost neutral while highly diverse populations are controlled by selection pressure. We discuss in detail the application of our results to human immunodeficiency virus population in vivo, sampling effects, and limitations of the model

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V3 Sequences of Paired HIV-1 Isolates from Blood and Cerebrospinal Fluid Cluster According to Host and Show Variation Related to the Clinical Stage of Disease

Cited by 84 publications

References 0 publications

Identification of Shared Populations of Human Immunodeficiency Virus Type 1 Infecting Microglia and Tissue Macrophages outside the Central Nervous System

Identification of Shared Populations of Human Immunodeficiency Virus Type 1 Infecting Microglia and Tissue Macrophages outside the Central Nervous System

Differences in human immunodeficiency virus type 1 V3 sequences from patients with and without AIDS dementia complex

Transition between Stochastic Evolution and Deterministic Evolution in the Presence of Selection: General Theory and Application to Virology

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